Predicting delays in lung cancer diagnosis and staging

Autor: Virginia Leiro‐Fernández, Cecilia Mouronte‐Roibás, Esmeralda García‐Rodríguez, Maribel Botana‐Rial, Cristina Ramos‐Hernández, María Torres‐Durán, Alberto Ruano‐Raviña, Alberto Fernández‐Villar, On behalf of the Lung Cancer Group at the Álvaro Cunqueiro Hospital in Vigo
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Thoracic Cancer, Vol 10, Iss 2, Pp 296-303 (2019)
Druh dokumentu: article
ISSN: 1759-7714
1759-7706
DOI: 10.1111/1759-7714.12950
Popis: Background Despite growing interest in increasing the efficiency and speed of the diagnosis, staging, and treatment of lung cancer (LC), the interval from signs and symptoms to diagnosis and treatment remains longer than recommended. The aim of this study was to analyze the factors that cause delays in the LC diagnosis/staging process and, consequently, delays in making therapeutic decisions. Methods We analyzed audit data from a prospective dataset of 1330 patients assessed at The Lung Cancer Rapid Diagnostic Unit from 26 June 2013 to 26 March 2016. The number and type of procedures and medical tests and the times of all procedures were recorded. Clinical and epidemiological variables and whether the diagnosis was performed on an inpatient or outpatient basis were also recorded. Results Malignancy was confirmed in 737 (55.4%) of the 1330 patients, with LC in 627 of these (85.2%). The mean interval to final diagnosis was 19.8 ± 13.9 days. Variables significantly related to a longer diagnostic time were the number of days until computed tomography (CT) was performed (odds ratio [OR], 95% confidence interval [CI] 1.347, 1.103–1.645; P = 0.003), until a histology sample was obtained (OR 1.243, 95% CI1.062–1.454; P = 0.007), and the total number of tests performed during the diagnostic and staging process (OR 1.823, 95% CI 1.046–3.177; P = 0.03). Conclusions A greater number of tests and more days to CT and histology led to longer delay times. Optimization of these factors should reduce delays in the LC diagnosis process.
Databáze: Directory of Open Access Journals
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